AI-based personalized e-learning systems: Issues, challenges, and solutions

M Murtaza, Y Ahmed, JA Shamsi, F Sherwani… - IEEE …, 2022 - ieeexplore.ieee.org
A personalized e-learning system is effective in imparting enhanced learning to its users. As
compared to a conventional e-learning system, which provides similar contents to each …

Predicting student outcomes in online courses using machine learning techniques: A review

A Alhothali, M Albsisi, H Assalahi, T Aldosemani - Sustainability, 2022 - mdpi.com
Recent years have witnessed an increased interest in online education, both massive open
online courses (MOOCs) and small private online courses (SPOCs). This significant interest …

A hybrid machine learning framework for predicting students' performance in virtual learning environment

E Evangelista - International Journal of Emerging Technologies in …, 2021 - learntechlib.org
Abstract Virtual Learning Environments (VLE), such as Moodle and Blackboard, store vast
data to help identify students' performance and engagement. As a result, researchers have …

Applications of Artificial Intelligence Models in Educational Analytics and Decision Making: A Systematic Review

J de Souza Zanirato Maia, APA Bueno, JR Sato - World, 2023 - mdpi.com
Education plays a critical role in society as it promotes economic development through
human capital, reduces crime, and improves general well-being. In any country, especially …

Forecasting of post-graduate students' late dropout based on the optimal probability threshold adjustment technique for imbalanced data

CL Rodríguez Velasco… - … Journal of Emerging …, 2023 - repositorio.unic.co.ao
The purpose of this research article was to contrast the benefits of the optimal probability
threshold adjustment technique with other imbalanced data processing techniques, in its …

The accuracy of machine learning models relies on hyperparameter tuning: student result classification using random forest, randomized search, grid search …

Y Rimal, N Sharma, A Alsadoon - Multimedia Tools and Applications, 2024 - Springer
Hyperparameters play a critical role in analyzing predictive performance in machine
learning models. They serve to strike a balance between overfitting and underfitting of …

[PDF][PDF] Convolutional neural network for predicting student academic performance in intelligent tutoring system

F Alshaikh, N Hewahi - … Journal of Computing and Digital Systems, 2024 - researchgate.net
One of the most significant research areas in education and Artificial Intelligence (AI) is the
earlier prediction of students' academic achievement. Limited studies have been conducted …

[PDF][PDF] Applications of artificial intelligence models in educational analytics and decision making: a systematic review

JSZ Maia, APA Bueno, J Sato - Available at SSRN 4264623, 2023 - papers.ssrn.com
Education plays a critical role in society because it promotes economic development
through human capital, reduces crime, and improves overall well-being. In any country …

Increasing the prediction power of moodle machine learning models with self-defined indicators

T Fauszt, L Bognár, Á Sándor - International Journal of Emerging …, 2021 - learntechlib.org
Starting with version 3.4 of Moodle, it has been possible to build educational ML models
using predefined indicators in the Analytics API. These models can be used primarily to …

Using artificial intelligence in education: decision tree learning results in secondary school students based on cold and hot executive functions

E Escolano-Perez, JL Losada - Humanities and Social Sciences …, 2024 - nature.com
Improving educational quality is a universal concern. Despite efforts made in this regard,
learning outcomes have not improved sufficiently. Therefore, further investigation is needed …